3D root scanner

We designed a 3D root scanner to capture images for 3D reconstruction of the root. The 3D root scanner utilizes ten industrial cameras mounted on a rotating curved frame to capture images from all sides of the maize root. Scanning of one maize root completes in five minutes.

Figure: 3D root scanner prototype. (a) 3D root scanner captures images of an excavated maize root grown under field conditions. (b) The stepper motor rotates the curved metal frame with the mounted cameras around the root. (c) The fixture keeps the root in place during scanning. (d) The adjustable camera shelves allow for the free positioning of each camera.

To operate the scanner, the root is fixed in the station stand. A stepper motor (Nema 34 CNC High Torque Stepper Motor 13Nm) drives a semicircular metal frame to rotate ten cameras around the root crown . We chose 12800 micro-step resolutions from among the 16 selectable options provided by the Digital Stepper Driver DM860I to convert the micro-steps to angle unit. We drilled 21 equidistant holes into the semicircular frame to provide flexible arrangement of each camera. A rail track along the semicircular frame allows for fine adjustment of the camera tilt and pan direction without compromising stability. The semicircular frame, along with ten low cost and highly versatile imaging cameras (Image Source DFK 27BUJ003 USB 3.0), can rotate around the root system to capture images up to 1-degree steps. The camera ships with the 1/2.3" Aptina CMOS MT9J003 sensor and can achieve high image resolution at 3856×2764 (10.7 MP) up to 7 fps.

The core unit of 3D scanner was Raspberry pi cluster, which was used to control the movement of step motor and synchronize the image caputring and step motor movement.

How to build raspberry pi supercomputer with raspberry pi cluster?

For the project, firstly select [Jessie], the Raspbian operating system based on Debian Linux for Raspberry Pi, as this not only comes with some goodies that are installed by default but it also allows to install all the components that may be required for the project.

Moving forward, the next step is to choose the programming language. In this case, select Python, as it has plenty of libraries available and also a nice integration with MPI via [mpi4py] library.

Building raspberry pi cluster

Check the list of items (links included) that you will need along with their prices.

Hardware requirements:

1. 10 x Rpi 3 model B 

2. 10 x 32Gb microSD card (Kingston)

3. 10 x USB to Micro USB Cable 0.5m 

4. 2 x Multi-Pi Stackable Raspberry Pi Case 

5. 1 x 16 port desktop switch

6. 10 x Ethernet cable 0.3m

7. 1 x USB Hub

Configuring your cluster of Raspberry pi

Basically, the idea is to configure one of the RPi's, then clone the SD card and later plug it to the next RPi. Below is a detailed description of the steps that you need to follow to get the device up and running:

Installing the OS

Download [Raspbian Jessie image]. You can download the zip file. However, if are facing problems downloading the zip file, you can use the torrent link instead.

Download [Win32DiskImager installer]. You need this to burn Raspbian image to your SD card.

Download [PuTTY] SSH client to connect to your RPi's.

Once the OS image is downloaded, burn it to the SD card using Win32DiskImager:

Plug the microSD card to the first Pi and power it up. Plug the Ethernet cable and return to your computer to access the Pi remotely.

Open a command prompt and type "ping raspberrypi". By default, the RPi's are named raspberrypi and can be easily spotted on the network. Once you ping it, you will be able to see the IP address of the device. Save this IP address for later use, as you will need it in PuTTY.

Launch PuTTY and type the IP address of the raspberrypi:

You should see something similar to the image below:

Login to your raspberry pi as: pi and password: raspberry (each RPi uses same login/password)

Type: sudo raspi-config to configure your device:

1. Go to Expand File System

2. Go to Advanced Options > HostName > set it to PiController

3. Go to Advanced Options -> MemorySplit > set it to 128

4. Go to Advanced Options > SSH > Enable

5. Finish and leave the configuration

Now, you can start installing MPICH3 and MPI4PY.

Installing MPICH3

Follow the steps mentioned at mpich3_mpi4_install.sh to install version 3.2 of MPICH:

or just execute one file ./mpich3_mpi4_install.sh

Once everything is installed, you should be able to see something like the image below:

Installing MPI4PY

Once everything is installed, you should be able to see something like the image below:

Now, the configuration of the first RPi is complete. Then, you will have to clone this SD card and put them into the other RPi's.

Preparing the other RPi's

As stated in the step above, bring the SD card to your main computer and save the content of the SD card using Win32DiskImager. Now, copy this new image to the other SD cards. You should have 4 SD cards with the same image now. Since, you now have 4 cloned SD cards, it would be advisable to plug every RPi individually and change the host name of every new added RPi into the network, for instance, pi01, pi02, pi03, etc. or you can name them the way you want.

Follow the steps mentioned below for adding every new RPi into the network:

pi01:

Use a [network scanner] to find the IP address of the newly added device. Once detected, use PuTTY to access it and use the commands below to set it up:

Type: sudo raspi-config to configure your device:

1. Go to Expand File System

2. Go to Advanced Options > HostName > set it to pi01

3. Go to Advanced Options > MemorySplit > set it to 16

4. Go to Advanced Options > SSH > Enable.

5. Finish and leave the configuration.

6. sudo reboot

Follow the same procedure for **pi02 **and pi03.

Once complete, you should be able to view all the 4 RPis using PuTTY and each RPi will have its own IP. Now, you need to store each IP address into a host file also known as machinefile. This file contains the hosts which start the processes on.

Go to your first RPi and type:

nano machinefile

Then, add the following IP addresses: (Note that you will have to add your own)

This will be used by the MPICH3 to communicate and send/receive messages between various nodes.

*In parallel computing, multiple computers or even multiple processor cores within the same computer are called nodes.

Configuring SSH keys for each RPi

Now, you need to be able to command each RPi without using users/passwords. To do this, you will have to generate SSH keys for each RPi and then share each key to each device under authorized devices. By doing this, MPI will be able to communicate with each device without bothering about credentials. Although this process is a bit monotonous, you will be able to run MPI without problems once it's completed.

Run the commands in sshKeysRpi.sh from the first Pi:

Just hit enter (if you don't want to add specific passphrase) when running the ssh-keygen, and the RSA key will be automatically generated for you.

Now, the link between the first Pi to every single device has been configured, however, you still need to configure the other way around. Hence, you will have to run the commands from every individual device in sshKeysIndividualRPi.sh:

Open the authorized_keys files and you will see the additional keys there. Each authorized_keys file on each device should contain 3 keys (as stated in the architecture diagram above).

Now, the system is ready for testing.

Note: If your IP address changes, the keys will be invalid and the steps will have to be repeated.

Testing the cluster

You can try the below small example to check if your cluster works as expected. If everything is configured correctly, the following command should work fine:

mpiexec --hostfile machinefile -n 4 hostname

You can see that each device has replied back and every key is used without problems.

Now, run the following command to test a helloworld example:

mpiexec -hostfile machinefile -n 4 python /home/pi/mpi4py-2.0.0/demo/helloworld.py

You should be able to see something like the image below:

Now, your system is ready to take any parallel computing application that you want to develop.

You can also build your own Raspberry Pi powered Linux computer.

Reference: https://www.techworm.net/2018/03/learn-build-supercomputer-raspberry-pi-3-cluster.html